Bug Prioritization to Facilitate Bug Report Triage

Canfora G, Cerulo L. Supporting change request assignment in open source development. In Proc. ACM Symposium on Applied Computing, Dijon, France, April 2006, pp.1767–1772.

Anvik J. Assisting bug report triage through recommendation [PhD Thesis]. University of British Columbia, 2007.

Cubranic D, Murphy C. Automatic bug triage using text categorization. In Proc. Software Engineering and Knowledge Engineering, Banff, Canada, June, 2004, pp.92–97.

Mozilla. http://www.mozilla.org , 2010.

Anvik J, Murphy G C. Determining implementation expertise from bug reports. In Proc. the 4th MSR, Minneapolis, USA, May 2007, Article No.2.

Tucek J, Lu S, Huang C, Xanthos S, Zhou Y. Triage: Diagnosing production run failures at the user’s site. ACM SIGOPS Operating Systems Review, 2007, 41(6): 131–144.

Herraiz I, German D M, Gonzalez-Barahona J M, Robles G. Towards a simplification of the bug report form in eclipse. In Proc. International Working Conference on Mining Software Repositories, Leipzig, Germany, May 2008, pp.145–148.

Anvik J. Automating bug report assignment. In Proc. the 28th International Conference on Software Engineering, Shanghai, China, May 2006, pp.937–940.

Weib C, Premraj R, Zimmermann T, Zeller A. Predicting effort to fix software bugs. In Proc. Workshop on Software Reengineering, Bad Honnef, Germany, May 2007.

Kim S, Whitehead J. How long did it take to fix bugs? In Proc. International Workshop on Mining Software Repositories, Shanghai, China, May 2006, pp.173–174.

Lamkanfi A, Demeyer S, Gigery E, Goethals B. Predicting the severity of a reported bug. In Proc. the 7th Working Conference on Mining Software Repositories, Cape Town, South Africa, May 2010, pp.1–10.

Yu L, Tsai W, Zhao W, Wu F. Predicting defect priority based on neural networks. In Proc. the 6th Int. Conf. Advanced Data Mining and Applications, Wuhan, China, November 2010, pp.356–367.

Kanwal J, Maqbool O. Managing open bug repositories through bug report prioritization using SVMs. In Proc. International Conference on Open-Source Systems and Technologies, Lahore, Pakistan, December 2010.

Kim S, Ernst M D. Prioritizing warning categories by analyzing software history. In Proc. the 4th International Workshop on Mining Software Repositories, Minneapolis, USA, May 2007, Article No. 27.

Kim S, Ernst M D. Which warnings should I fix first? In Proc. the 6th ESEC-FSE, Dubrovnik, Croatia, September 2007, pp.45–54.

Kremenek T, Engler D. Z-Ranking: Using statistical analysis to counter the impact of static analysis approximations. In Proc. the 10th International Conference on Static Analysis, June 2003, pp.295–315.

Anvik J, Hiew L, Murphy G C. Who should fix this bug? In Proc. the 28th International Conference on Software Engineering, Shanghai, China, May 2006, pp.361–370.

Anvik J, Murphy G C. Reducing the effort of bug report triage: Recommenders for development-oriented decisions. ACM Transactions on Software Engineering and Methodology, 2011, 20(3): Article No.10.

Aljarah I, Banitaan S, Abufardeh S, Jin W, Salem S. Selecting discriminating terms for bug assignment: A formal analysis. In Proc. the 7th International Conference on Predictive Models in Software Engineering, Banff, Canada, September 2011, Article No.12.

Ahsan S N, Ferzund J, Wotawa F. Automatic software bug triage system (BTS) based on Latent Semantic Indexing and Support Vector Machine. In Proc. the 4th International Conference on Software Engineering Advances, Washington, USA, September 2009, pp.216–221.

Jeong G, Kim S, Zimmermann T. Improving bug triage with bug tossing graphs. In Proc. the 7th ESEC-FSE, Amsterdam, Netherlands, August 2009, pp.111–120.

Tamrawi A, Nguyen T, Al-Kofahi J, Nguyen T N. Fuzzy set-based automatic bug triaging. In Proc. the 33 rd International Conference on Software Engineering (NIER Track), Miami, USA, May 2011, pp.884–887.

Lamkanfi A, Demeyer S, Soetens Q D, Verdonck T. Comparing mining algorithms for predicting the severity of a reported bug. In Proc. the 15th European Conference on Software Maintenance and Reengineering, Oldenburg, Germany, March 2011, pp.249–258.

Ling C, Huang J, Zhang H. Auc: A better measure than accuracy in comparing learning algorithms. In Lecture Notes in Computer Science 2671, Xiang Y, Chaib-Draa B (eds.), Springer-Verlag, 2003, pp.329–341.

Gegick M, Rotella P, Xie T. Identifying security bug reports via text mining: An industrial case study. In Proc. the 7th Working Conference on Mining Software Repositories, Cape Town, South Africa, May 2010, pp.11–20.

Zaman S, Adams B, Hassan A E. Security versus performance bugs: A case study on Firefox. In Proc. the 8th Working Conference on Mining Software Repositories, Hawaii, USA, May 2011, pp.93–102.

Runeson P, Elexandersson M, Nyholm O. Detection of duplicate defect reports using natural language processing. In Proc. the 29th International Conference on Software Engineering, Minneapolis, USA, May 2007, pp.499–510.

Wang X, Zhang L, Xie T, Anvik J, Sun J. An approach to detecting duplicate bug reports using natural language and execution information. In Proc. the 30th International Conference on Software Engineering, Leipzig, Germany, May 2008, pp.461–470.

Canfora G, Cerulo L. Impact analysis by mining software and change request repositories. In Proc. the 11th International Software Metrics Symposium, Como, Italy, September 2005, Article No.29.

Prifti T, Banerjee S, Cukic B. Detecting bug duplicate reports through local references. In Proc. the 7th International Conference on Predictive Models in Software Engineering, Banff, Canada, September 2011, Article No.8.

Wu L, Xie B, Kaiser G, Passonneau R. BugMiner: Software reliability analysis via data mining of bug reports. In Proc. the 25th International Conference on Software Engineering and Knowledge Engineering, Miami, USA, July 2011, pp.95–100.

Marks L, Zou Y, Hassan A E. Studying the fix-time for bugs in large open source projects. In Proc. the 7th International Conference on Predictive Models in Software Engineering, Banff, Canada, September 2011, Article No.11.

Gyimothy T, Ferenc R, Siket I. Empirical validation of object-oriented metrics on open source software for fault prediction. IEEE Transactions on Software Engineering, 2005, 31(10): 897–910.

Zimmermann T, Premraj R, Zeller A. Predicting defects for Eclipse. In Proc. International Workshop on Predictor Models in Software Engineering, Minneapolis, USA, May 2007, Article No.9.

Bugzilla. http://www.bugzilla.org , 2010.

Han J, Kamber M. Data Mining: Concepts and Techniques. 2nd edition, Morgan Kaufmann, 2006.

Joachims, T. Text categorization with support vector machines: Learning with many relevant features. In Proc. European Conference on Machine Learning, Chemnitz, Germany, April 1998, pp.137–142.

Kantardzic M. Data Mining: Concepts, Models, Methods, and Algorithms. New York, USA: Wiley-Interscience, 2003.

Witten H I, Frank E. Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. New York, USA: Morgan Kaufmann, 2000.

Noble W S. What is a support vector machine? Nature Biotechnology, 2006, 24: 1565–1567.

Vapnik V N. Statistical Learning Theory. New York, USA: Wiley-Interscience, 1998.

Sebastiani F. Machine learning in automated text categorization. ACM Computing Surveys, 2002, 34(1): 1–47.

Eclipse. http://www.eclipse.org , 2010.

Panjer L D. Predicting Eclipse bug lifetimes. In Proc. the 4th International Workshop on Mining Software Repositories, Minneapolis, USA, May 2007, pp.1–8.

Baeza-Yates R, Ribeiro-Neto B. Modern Information Retrieval. Boston, USA: Addison-Wesley Longman, 1999.

GNATS. http://www.gnu.org/software/gnats , 2010.

JIRA. http://www.atlassian.com/software/jira , 2010.